Supervised independent component analysis as an alternative method for genomic selection in pigs

• Autor(a) principal: Azevedo, C.F.
• Data de Publicação: 2014
• Outros Autores: Silva, F.F., Resende, M.D.V. de, Lopes, M.S., Duijvesteijn, N., Guimarães, S.E.F., Lopes, P.S., Kelly, M.J., Viana, J.M.S., Knol, E.F.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: LOCUS Repositório Institucional da UFV
• Texto Completo: http://dx.doi.org/10.1111/jbg.12104; http://www.locus.ufv.br/handle/123456789/16058
• topic: Accuracy; SNP; Animal breeding; Genomic selection

The objective of this work was to evaluate the efficiency of the supervised independent component regression (SICR) method for the estimation of genomic values and the SNP marker effects for boar taint and carcass traits in pigs. The methods were evaluated via the agreement between the predicted genetic values and the corrected phenotypes observed by cross-validation. These values were also compared with other methods generally used for the same purposes, such as RR-BLUP, SPCR, SPLS, ICR, PCR and PLS. The SICR method was found to have the most accurate prediction values.